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Twins With Specific vs. Traditional Fetal Growth Charts (TWiST)

Indiana University logo

Indiana University

Status

Not yet enrolling

Conditions

Twin Pregnancy

Treatments

Other: Twin-Specific Growth Chart Interpretation
Other: Singleton-Based Growth Chart Interpretation

Study type

Interventional

Funder types

Other

Identifiers

Details and patient eligibility

About

This study aims to compare how well two different types of fetal growth charts work in tracking the growth of twins during pregnancy. These charts help doctors decide if a fetus is growing normally. One type is commonly used for all pregnancies, while the other is specially designed for twin pregnancies. The study will enroll pregnant individuals carrying twins. Participants will be randomly assigned to have their care guided by either the traditional chart or the twin-specific chart. Researchers will compare outcomes such as birth weight, timing of delivery, and newborn health. The goal is to find out if using twin-specific charts can improve care and reduce unnecessary interventions.

Full description

Twin pregnancies are at increased risk for growth abnormalities and adverse perinatal outcomes. Despite physiological differences in fetal growth patterns between singleton and twin pregnancies, most clinical decisions in the United States still rely on singleton-based fetal growth charts. This randomized controlled trial (RCT) evaluates whether using twin-specific fetal growth charts to guide clinical care results in better perinatal outcomes compared to using standard singleton-based charts.

Participants will be pregnant individuals with twin gestations receiving routine prenatal care at participating clinical sites. Eligible participants will be randomized to one of two groups: (1) management based on singleton growth charts or (2) management based on twin-specific charts. Both charts will be used to assess fetal growth during ultrasound visits, but only the chart assigned to the participant's group will inform clinical decision-making. Data will be collected on outcomes including birth weight, small-for-gestational-age (SGA) classification, gestational age at delivery, NICU admissions, and neonatal morbidity.

The study aims to determine whether using twin-specific fetal growth standards can reduce the overdiagnosis of growth restriction and the associated risks of iatrogenic preterm delivery and unnecessary interventions. Results may support more tailored approaches to growth assessment in twin pregnancies.

Enrollment

150 estimated patients

Sex

Female

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Pregnant individuals with a twin pregnancy of at least 18 weeks gestation.
  • Willing and able to provide informed consent.
  • Planning to deliver at a participating center.

Exclusion criteria

  • Major fetal anomalies or known aneuploidy.
  • Significant maternal medical conditions that might confound study outcomes.
  • Inability to comply with study procedures.

Trial design

Primary purpose

Diagnostic

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

150 participants in 2 patient groups

Twin-Specific Growth Chart Group
Experimental group
Description:
Participants in this arm will receive prenatal ultrasound assessments interpreted using a twin-specific growth chart for estimated fetal weight and biometry. Clinical decisions and perinatal risk assessments will be guided based on twin-specific percentiles.
Treatment:
Other: Twin-Specific Growth Chart Interpretation
Singleton-Based Growth Chart Group
Active Comparator group
Description:
Participants in this arm will receive prenatal ultrasound assessments interpreted using a singleton-based growth chart for estimated fetal weight and biometry. Clinical decisions and perinatal risk assessments will be based on singleton percentiles, which represent standard practice in many settings.
Treatment:
Other: Singleton-Based Growth Chart Interpretation

Trial contacts and locations

0

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Central trial contact

Emrah Aydin, MD, PhD, MBA, MSc

Data sourced from clinicaltrials.gov

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